# lecture18 - Motion Estimation Why estimate motion? Lots of...

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Motion Estimation

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Why estimate motion? Lots of uses Motion Detection Track object behavior Correct for camera jitter (stabilization) Align images (mosaics) 3D shape reconstruction Video Compression
Optical flow Measurement of motion at every pixel

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Optical flow An image from Hamburg Taxi Sequence
Video Mosaics

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Video Mosaics
Video Mosaics

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Video Compression
Geo Registration

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Video Segmentation
Structure From Motion

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Optical flow Measurement of motion at every pixel
Problem definition: optical flow How to estimate pixel motion from image H to image I? Solve pixel correspondence problem given a pixel in H, look for nearby pixels of the same color in I Key assumptions color constancy : a point in H looks the same in I – For grayscale images, this is brightness constancy small motion : points do not move very far This is called the optical flow problem

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Optical flow constraints (grayscale images) Let’s look at these constraints more closely brightness constancy: Q: what’s the equation? small motion: (u and v are less than 1 pixel) suppose we take the Taylor series expansion of I:
Optical flow equation Combining these two equations In the limit as u and v go to zero, this becomes exact

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Optical flow equation Q: how many unknowns and equations per pixel?
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## This note was uploaded on 06/12/2011 for the course CAP 5415 taught by Professor Staff during the Fall '08 term at University of Central Florida.

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lecture18 - Motion Estimation Why estimate motion? Lots of...

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